public void ValueIsStoredCorrectly()
{
int a = 4;
var allele = new Allele <int>(a);
Assert.Equal(a, allele.GetValue());
}
public void MutationDistributionDoesNotDepartFromNormalDistributionInLogSpace()
{
// Build up unbounded domain.
var domain = new LogDomain(1.0 / double.MaxValue, double.MaxValue);
// Fix the value to mutate and the variance percentage.
Allele <double> valueToMutate = new Allele <double>(3.4);
double variancePercentage = 0.000001;
// Collect results in log space for a lot of mutations.
int numberRuns = 1000;
double[] mutationsInLogSpace = new double[numberRuns];
for (int i = 0; i < numberRuns; i++)
{
mutationsInLogSpace[i] = Math.Log((double)domain.MutateGeneValue(valueToMutate, variancePercentage).GetValue());
}
// Apply the Kolmogorov-Smirnov test.
double stdDev = Math.Sqrt(variancePercentage * (Math.Log(domain.Maximum) - Math.Log(domain.Minimum)));
KolmogorovSmirnovTest normalityTest = new KolmogorovSmirnovTest(
sample: mutationsInLogSpace,
hypothesizedDistribution: new NormalDistribution(mean: Math.Log(valueToMutate.GetValue()), stdDev: stdDev));
Assert.False(
double.IsNaN(normalityTest.PValue) || normalityTest.Significant,
$"Mutation was found to be not normal by the Kolmogorov-Smirnov test with significance level of {normalityTest.Size}.");
}
public void MutationDistributionDoesNotDepartFromNormalDistribution()
{
// Build up unbounded domain.
this._continuousDomain = new ContinuousDomain();
// Fix the value to mutate and the variance percentage.
Allele <double> valueToMutate = new Allele <double>(3.4);
// Divide by 2 to prevent overflows. Want: 0.5 / (max - min)
double variancePercentage =
(0.5 / 2) / ((this._continuousDomain.Maximum / 2) - (this._continuousDomain.Minimum / 2));
// Collect results of a lot of mutations.
double[] mutations = new double[ContinuousDomainTest.TriesForRandomTests];
for (int i = 0; i < ContinuousDomainTest.TriesForRandomTests; i++)
{
mutations[i] =
(double)this._continuousDomain.MutateGeneValue(valueToMutate, variancePercentage).GetValue();
}
// Apply the Kolmogorov-Smirnov test.
double stdDev = Math.Sqrt(0.5);
KolmogorovSmirnovTest normalityTest = new KolmogorovSmirnovTest(
sample: mutations,
hypothesizedDistribution: new NormalDistribution(mean: valueToMutate.GetValue(), stdDev: stdDev));
Assert.False(
double.IsNaN(normalityTest.PValue) || normalityTest.Significant,
$"Mutation was found to be not normal by the Kolmogorov-Smirnov test with significance level of {normalityTest.Size}.");
}
public void GenerateRandomGeneValueDoesNotDepartFromUniformDistributionInLogSpace()
{
// Build up logarithmically spaced domain from e to e^10.
double minimumExponent = 1;
double maximumExponent = 10;
var domain = new LogDomain(Math.Exp(minimumExponent), Math.Exp(maximumExponent));
// Collect results of value generation.
int numberRuns = 10000;
double[] generatedValues = new double[numberRuns];
for (int i = 0; i < numberRuns; i++)
{
Allele <double> generated = domain.GenerateRandomGeneValue();
generatedValues[i] = Math.Log(generated.GetValue());
}
// Apply the Anderson-Darling test.
AndersonDarlingTest uniformTest = new AndersonDarlingTest(
generatedValues,
new UniformContinuousDistribution(minimumExponent, maximumExponent));
Assert.False(
uniformTest.Significant,
$"Random generation was found to be not uniform in log space by the Anderson-Darling test with significance level of {uniformTest.Size}.");
}
public void GenerateRandomGeneValueDoesNotDepartFromUniformDistribution()
{
// Create domain.
ContinuousDomain domain = new ContinuousDomain(ContinuousDomainTest.minimum, ContinuousDomainTest.maximum);
// Collect results of value generation.
double[] generatedValues = new double[ContinuousDomainTest.TriesForRandomTests];
for (int i = 0; i < ContinuousDomainTest.TriesForRandomTests; i++)
{
Allele <double> generated = domain.GenerateRandomGeneValue();
generatedValues[i] = generated.GetValue();
}
// Apply the Anderson-Darling test.
AndersonDarlingTest uniformTest = new AndersonDarlingTest(generatedValues, new UniformContinuousDistribution(ContinuousDomainTest.minimum, ContinuousDomainTest.maximum));
Assert.False(
uniformTest.Significant,
$"Random generation was found to be not uniform by the Anderson-Darling test with significance level of {uniformTest.Size}.");
}